Last 2005, Mr. Wm. A. Wulf, president of the National Academy of Engineering, and the AT&T Professor of Engineering and Applied Science in the Department of Computer Science at University of Virginia was invited in the House of Science to deliver some points about the current state of Computer science research. There he delivered four points of interest, the first of which is he took it out from the Science the Endless Frontier, the report that established our system of federal funding of basic research, Vannever Bush advocated a system in which the government funds research, but the research to be done is selected on its merit by the researchers themselves. He said that such a system would pay dividends to the nation in national security, prosperity, and health. It is hard to think of a better “poster child” for the truth of this assertion than Computer Science. Consider the abbreviated list:

All of these were made possible by the federal investment in long-term, basic computing research. Like Mr.Wulf, I believe that it is a mistake to think of such funding as an “expense” and it must be regarded as an investment that demonstrably has had a huge return! Technology such as that listed above is the return on the investments made a decade or more ago. Investments made today in research will have equally large returns for our children and grandchildren; conversely, it is our children and grandchildren that will pay if we do not make them now.

Second, computing and computer science is in the unusual position of being both a challenging intellectual discipline in itself, and providing an infrastructure for other fields of science, engineering, and commerce. While the benefits to society listed above can be directly attributed to computer science, there are also many more benefits that have resulted from the use of computing in everything from cosmology, to weather prediction, and to health care. Across this broad spectrum, computer science has enabled a better quality of life for us all. This simply reinforces the notion that funds expended on computing research are demonstrably investment, not expense. They are, in fact, an investment with an enormous multiplier because advances in computing and information technology have immediate, direct and tangible benefits on virtually all human activities.

Thirdly, the idea that basic research begets applied research begets development begets benefits to society is both wrong and counter-productive when applied to public policy decisions. Instead, there is a marvelously rich and productive interplay between basic scientific discovery and application, between universities and industry, between societal need and technology. The bottom line, however, is that if federally-funded, university-based basic research weren’t “in the loop”, these enormously beneficial technologies would not exist. Basic research may not be the original source for all the benefits we enjoy from technology, but it is a vital and irreplaceable component of the rich system that produces them.

Lastly, computer science research is for and about the people. If computing research has a large multiplier because of its broad application, then the people capable of doing that research are yet another multiplier on top of that! Disinvestment in university-based research is a disinvestment in the production of the next generation of people, with far greater negative impact than simply the loss of the research.

In these points raised by Mr. Wulf we can see that at those times the funding for computer science research was being talked over by the government, specifically the US government. As a summary, the government is still arguing whether continued funding for such researches would be beneficial for both government and people. And as Mr. Wulf pointed out, with the proper research support and funding to universities and colleges across the country or even across the globe is beneficial to all, maybe not today but certainly for tomorrow.

Mr. Wulf also stressed the importance of cybersecurity. At that time, PITAC strongly identified the need for a better funded and stable program of long term basic research. The dominant model of cybersecurity, namely a perimeter defense, is flawed and incremental patches to it will never result in the level of security we need for today’s systems, much less the increased dependence we should expect for future ones. This is an excellent example where boldness and courage are needed, and hence where the perception of excessively low proposal success rates can have severe consequences. He emphasized that the future of researches is greatly affected by the resources available, in the mean point, funding is a great issue. New ideas are needed, just as in cybersecurity research, but instead of temerity, conservatism was imposed. Decline in the success rates of proposals indeed has a significant negative impact, however, we must have the courage to explore things and open for discoveries and innovations. One of the highlights of his words is that the thought of research funding is not merely an expense but instead it is an investment.

But on my research today, the government funding to computer science research now leads to the new trend of studying Green Computing. Go to IT related company webpages, search in the Internet or simply read IT magazines and you can see that the trend is going “green. Computers were and are still aiding people for more comfortable life but we can’t deny the fact that at some point the environment is compromised with these advances. Today, consumers are looking for products with good quality but eco friendly and energy efficient which lead to more research about this topic. Computer science researches are going for greener data centers, monitors, hardware and even researches for green softwares. Also, researches for creating products that might lessen the negative effects of computer radiation is also on going. Computers release electromagnetic field radiation.

This EMF is actually a type of radiation. It isn’t the same type as uranium or plutonium; rather, it is a non-ionizing radiation. This means that the emitted radiation is not strong enough to remove electrons, or ionize the atoms. Instead, it just excites the electrons. It already sounds a little Different devices emit different types and amounts of this EMF radiation. But then past and ongoing researches are trying to prove that these is still harmful since it can also premature cell division. The cells actually divide before the DNA is correctly established, which may possibly lead to mutation or can also bring cancer especially for those who have been in contact with computers in a long time (referring to years).

In past, computer science research tends to focus more on using and improving technology. Making it more flexible for implementation of different purposes, beneficial in different areas such as security, defense, healthcare or medicine, and education but nowadays it leans more on ways to make it more eco friendly but not comprising the quality and services it was built to do.

These are the Technical Topics in which Computer Science Researches are now focused:

Subject: Current State of CS Research and Hot CS Research Topics Tue Jul 21, 2009 12:20 pm

According to Shingo Takada, Ph. D., the effect of technology on our daily lives is constantly increasing. Researches in computer science, including communication, create advances that will have a profound effect on our lives. By profound we mean deep and intense. It is no longer a wonder why technology is very fast-paced because we know that different, even simultaneous, researches are being done to improve it.

In the United States, Wm. A. Wulf, Ph. D, stated in a congressional session that the federal investments in computing research helped greatly in improving the state of computer science research. Research has also given way to collaborations between universities, industries and the government. Reading this, I felt somewhat envious. If only the Philippines were this supportive of research then we’d have been on the path towards building a better nation.

According also to a study conducted by Debray, et. al, there is an increasing involvement of undergraduates in computer science research and we are a proof of that. I believe that this is good news because it has been a common misconception that research is a field for the experts (in other words, elders. ). At least, the field of research is slowly but surely being explored by younger generations and the fresh ideas that they have will contribute greatly to quicker advancements.

This next part, I hope, will be of help to us in our quest for research topics. Since I know that most of us are at a loss for topics to propose, the items I will give below can possibly give us an idea. Almost all of the resources I found mentioned closely identical topics in computer science research. However, I will use the outline provided by Takada, Ph. D. in his Computer Science and Communication Technology course presentation.

The first area that is considered “hot” or “in” in computer science research is Computer Hardware. Since computer hardware is the basic component of a computer system, it is not surprising that this area is included in the spotlight of research topics. Many advances in technology involve hardware in one way or another and it is only fitting to improve the quality of technology. I mean, what would become of a good software if the hardware cannot even keep up with it? Results of interest in this research area include the many fast-evolving gadgets that we have. Every now and then, an enhanced version of our gadgets comes out and newly-purchased gadgets become obsolete as soon as they were bought.

The second area of research is Software Engineering. I can relate to this mostly because we had undergone and are currently taking up the subject Software Engineering. Software is another basic component of a computer system, and most of technology for that matter, and I believe that there is no question that this is a very good research area in computer science. This is where our programming and software development skills can be harnessed, together with hardware, to come up with innovative solutions to the increasing problems in our daily lives. As I write this, I am thinking from the back of my mind, about the system we are currently developing for the University. RSG once mentioned that when we complete the development of all our systems, they can be presented as a big research proposal to the University.

Another “hot” topic in computer science research is Computer Human Interaction. This is a very important field in research since we deal with technology every day. It would be nice to interact with technology that is flexible and able to meet most of our demands. This topic actually made me think of Virtual Agents in customer management. Virtual agents are programmed to respond appropriately to the customers’ queries and statements. Inappropriate responses may cause the organization using the virtual agent to lose their customers. I believe that further research on this topic will be very helpful so that we can make computer-human interaction as smooth and as natural as possible.

The next area of interest in computer science research is Database. Almost all organizations use databases to store their files and records. Folders and cabinets are a thing of the past because of advances made in database technology. Since database deals with electronic data and thus there is a factor of volatility, I believe that further research in this area will contribute greatly to the confidentiality, integrity, and availability of information. Even in class, we try to come up with database solutions to solve the record-keeping and management problems of various individuals or organizations so this is not a foreign topic to us.

Image processing (some include audio and video processing in this area) is another hot topic in computer science research. I have personally observed that more and more applications become dependent on graphics of some sort. Since this is the case, research on image processing is only beneficial in order to improve the quality of images that is delivered to the users. Another particular area of keen interest is the conversion of images into formats that will not destroy or degrade their quality.

Another area in the research spotlight is ITS or Intelligent Transportation System. I am not very familiar with this topic since this is the first time I have heard of it. However, I will try to elaborate on it based on my readings. According to Wikipedia, ITS refers to efforts to add information and communications technology to transport infrastructure and vehicles in an effort to manage factors that typically are at odds with each other, such as vehicles, loads, and routes to improve safety and reduce vehicle wear, transportation times, and fuel consumption. As amazing as it may sound, I am not very interested in this topic simply because there is a reduced need for transportation due to the advent of the Internet. But I guess this is probably helpful when it comes to large corporations.

Finally, Theory is still considered a hot research area. Even though most of what we do now is application, theory is still important to build up the foundation of technology. Theory is where it all began – from papers and assumptions. This is where we try to look for problems, gather relevant information and hypothesize. Application is the implementation and actual testing to validate a certain theory. It is possible that without theoretical research, innovations would also stop.

There are many more areas in computer science research but the ones I listed above are the most recent and interesting. However, I believe that it does not matter which area of research we are interested in. After all, no matter what we choose, our goal is still the same – to improve the quality of life.

Computer Science Researches has done many great things to improve lifestyles here on earth. Although computer science researches may have seen to be the core foundation for tomorrows’ foundation for development, it is still facing many problems that are oblivious to a person who is blinded by the impact it has brought. Computer Science Research could be the very beginning of future technological development. It has touched every single inch of areas they could examine and apply corresponding studies they could think of. Researchers are growing rapidly to cope up to the fast evolution of technologies and to the needs of the user.

Computer Science has been thought of as way of getting rich that is why many students have enrolled in this field. Schools and universities had crosses its boundaries. There are people who are engaged in researching from students to teachers. Also, the government has over-funded the life of science research because they think computer increases our intelligence, not our life span. This kind of approach to computer science researches would really work well since different aspects would be traced by different disciplines.

I have a friend who keeps on telling me that computer science researches could really go a long way in inventing something that could really improve the way we live. No one knows that with just a blink of an eye computer science researches could be one of the ways to take hold of immortality.

The article I have read is about the computer science research conducted by the research and development department in University of Georgia. They were trying to intersect computer science to almost all branches of sciences addressing the most difficult state in managing data and information as well as in providing algorithms that can be used to get the optimal solutions in any difficult problems. The department of computer Science in University of Georgia has faculties whose interest cover many of the growing and emerging research areas in computer Science. Particular strength includes theory, systems, information systems, and artificial intelligence. The application of computer science have been a big step to any field of specialties, from a traditional state processes to a more automated and systematic one, promising a great chance for progress and expansion of each field in terms of heir capability and scope.

One example of these researches is artificial intelligence, which also awakens my interest. Perhaps, we already know that artificial intelligence is the computer modeling of intelligent behavior, including but not limited to modeling the human mind. Artificial intelligence can be called as intelligent agents that demonstrate the functional essence of intelligent. Artificial intelligence is a science and engineering of making intelligent machines. The core areas of researches like these are about the presentation of knowledge, reasoning and learning, planning and decision making. It seeks to enable computers and machines to mimic human intelligence and sensory processing ability, and models human behavior with computers to improve our understanding of intelligence.

Another area of computer science that has found wide practical use is robotics, the design and development of computer controlled mechanical devices. Robots range in complexity from toys to automated factory assembly lines and relieve humans from tedious, repetitive, or even dangerous task. Robots are also employed where requirements of speed, precision, consistency, or cleanliness exceed what humans can accomplish.

The main focus of the robotics research group is the development of autonomous mobile robots (AMRs). With AMRs there are two primary issues to deal with: (1) cognitive behavior, and (2) motion. Cognitive behavior addresses problem solving using sensory inputs and desired goals. Motion deals with aspects of movement from simple robotic arm movement to autonomous rovers in unknown environments. Cognitive behavior is the current focus of the research group. Two projects currently underway involve on-board image processing of video camera inputs for decision making, and the development of an evolutionary computing approach to controller configuration (possibly using field programmable gate arrays). In addition, the controller evolution project is attempting to provide for automatic (rule directed) behavior specification.

Scientist involved in the field of robotics study the many aspects of controlling robots. These aspects includes modeling the robot’s physical properties, modeling its environment, planning its actions, directing its mechanisms efficiently, using sensors to provide feedback to the controlling program, and ensuring the safety of its behavior. They also study ways of simplifying the creation of control programs. One area of research seeks to provide robots with more of the dexterity and adaptability of humans, and is closely associated with AI.

According to Ronald Arkin, director of the mobile robot laboratory at Georgia Institute of Technology, “Robots are good explorers because you don’t have to deal with life support systems that human would need. They’re easier to take care of and much more adaptable for hostile environments than people.” The presence of this technology is also making its name in our usual standard of living.

It’s really true that the intelligence of human is beyond what we can imagine. I remember a Japanese drama series entitled ‘absolute Boyfriend’. It was all about a new invention of Mr. Namikiri, using a revolutionary system it will ensure the happiness of the next generation. A robot solely dedicated to love. Love is by nature a sorrowful thing, and with this robot, there won’t be any more women suffering. Having these kind of ideal boyfriend type, life will really change. But it turns out that this robot develop real human emotions enabling him to truly love Riiko but also resulting in system malfunctions. It started having a will of his own and a heart that feels love. But is it really true that a robot that possesses emotions, intelligence, consciousness, and ego is a broken machine and defective merchandise or the programming of the one who invented it was just fantastic and intelligent?

Above all these, I was amazed of the rapid progress of the development of computer science researches. Not only in the production of excellent computer systems and developing programming languages but also it is spreading its limitations of work to become more functional in any fields of life.

The insights that I gained was based on the article that I read entitled “Research in Computer Science: An Empirical Study.” The study was made by the researchers to examine the state of Computer Science (CS) research. It was also their objective to provide a detailed characterization of CS Research. The said examination regarded the following: (1) the topics, (2) research approaches, which refer to the way research study is conducted, (3) research methods, (4) reference disciplines, which refer to the theoretical foundation of the research, and (5) levels of analysis that CS researchers use, which refer to the object that is studied. And by examining 628 papers published between 1995 and 1999 in 13 leading research journals, they were able to produce results and come up with a conclusion.

To characterize research in CS, the first thing that the researchers did was to identify a classification scheme that would enable them to capture the richness of CS research. They found out that traditional classification schemes tend to focus on topic with research method as their secondary consideration. And because none of the existing classification schemes was sufficiently rich in the desired dimensions, they developed a multi-faceted classification system that characterizes research along the five (5) dimensions given above. The said classification system was developed to describe research in three computing-related disciplines: Computer Science (CS), Software Engineering (SE), and Information Systems (IS).

In classifying topic, the researchers used several sources of topics from the general discipline of computing to ensure that their list of topics was sufficiently broad to include all areas of computing research. Their classification scheme divided the topics of computing research field into several major categories: problem-solving concepts, computer concepts, systems/software concepts, data/information concepts, problem-domain-specific concepts, systems/software management concepts, organizational concepts, societal concepts, and disciplinary issues. Each of the categories was further divided into several subordinate categories.

The researchers also categorized the research techniques used. The techniques were divided into research approach which refers to the overall approach undertaken in performing the research and research method which is the more detailed techniques used. The four major research approaches such as descriptive, developmental, formulative and evaluative that were characterized by the analysis of articles made in SE and IS between 1986 and 1991 were subdivided by the researchers into categories. They also included developmental into descriptive category because such research involved describing systems.

The descriptive research approach has three subcategories: sub-category descriptive system (DS) that was based on Morrison and George’s descriptive category that is used to capture papers whose primary focus is describing a system, descriptive-other (DO) that is used to capture papers that used descriptive approach for describing something other than a system and descriptive-review (DR) whose primary content is a review of the literature.

The formulative research approach was subcategorized into six, the rich set of possible entities being formulated which includes processes, procedures, methods, algorithms, frameworks and guidelines/ standards. The researchers based the three subcategories under evaluative research approach on the three alternative evaluative epistemologies identified by Orlikowski and Baroudi in 1991. These subcategories were the following: positivist (evaluative-deductive in their system), interpretive (evaluative-interpretive), and critical (evaluative-critical).

After classifying research approach, let us now proceed to the research method. Research method, as stated, is the more detailed techniques used. Unlike research approach, research method has numerous classifications to choose. The researchers stated in the paper that the computing discipline that most concerned with research method is the IS. Many prior publications identified a number of commonly used methods such as laboratory experiments, field studies, case studies, field experiment, conceptual analysis or conceptual study, literature review, instrument development, and exploratory survey. Glass in 1995 categorized methods as scientific, engineering, empirical, and analytical. The researchers also added the following categories of the CS component of computing research: conceptual analysis/mathematical (CA/M) and mathematical proof to characterize papers that use mathematical techniques, simulation to characterize papers that use simulation as their primary research method, concept implementation to characterize papers that demonstrate proof of a concept by building a prototype system, and laboratory experiment (software) to characterize papers that compare the performance of the newly-proposed systems with the existing systems.

Reference disciplines refer to the disciplines such as theory that provide an important basis for the research that is being conducted. The paper cited the following research disciplines for Information Systems: computer science, management science, and cognitive science, organizational science, and economics, behavioral science, organizational theory, management theory, language theories, artificial intelligence, ergonomics, political science, and psychology, mathematics/statistics and engineering.

The level of analysis refers to the idea that a research may be conducted at several in which the nature of a research may be technical or behavioral. The research would focus on the computing system (CS), computing element (CE) or abstract concept level. Such researches are examples of technical research.

-------- The study of the researchers showed that research in computer science was fairly distributed among the five categories: computer concepts, problem-domain-specific concepts, systems/software concepts, data information concepts, and problem-solving concepts. The leading category was the computer concepts followed by problem-domain-specific concepts. Computer graphics/pattern analysis was the leading sub-category which is part of problem-domain-specific concepts. Next to it was the inter-computer communication part of computer concepts which includes topics such as:

o networking and distributed systemso computer hardware principles/architecture, which is part of computer concepts alsoo database/warehouse/mart organization, which is part of data/information conceptso mathematics/computational science, which is part of problem-solving concepts

The study also showed that some of the journals that they studied focused on the same topic area and that most journals tended to have a single main topic as suggested by their title. With regard to the research approach, most of the researchers used the formulative approach followed by evaluative and descriptive research approach. Thus, the focus in most areas in CS research is primarily on formulating things. The primary research method that CS researchers used was the Conceptual Analysis/Mathematical (CA/M). Next to it was the Conceptual Analysis.The most dominant level of analysis was the Computing Element (CE) category followed by Abstract Concept (AC), then the rest followed. Based on their examined papers, computer science itself was used as reference discipline and the other discipline was mathematics.

Researchers also concluded that CS research addresses a diverse range of topics and that there is a high degree of consistency in terms of the research approaches, research methods, and levels of analysis used to study these topics.

I was able to read the same article that Sheryl had read (actually I have read it long before she posted her answer..hehe). The title of the study that the researchers made is Research in Computer Science: An Empirical Study, wherein they are able to study and examine further computer science research and their main concern is to be able to know the TOPICS that computer science research address, the APPROACH being used in conducting CS research, the METHOD being used by the researchers, their reference discipline and finally, their level of analysis. This study goes around with these five major points. The researchers are able to discover that while computer science research examines a variety of technical topics, it is relatively focused in terms of level at which research id conducted as well as the research technique used. Further, CS research seldom relies on work outside the discipline for its theoretical foundations. They are able to come up with this conclusion after examining six hundred twenty eight published CS research in thirteen leading CS research journals in the CS fields. Everything that I will share is based on what I have read and what I will write is all from this study. I will no longer emphasize that this is from the researchers; I will talk and write on their behalf.

First thing is the topic/s being address by CS researchers. The classification of topics is divided into several major categories and subcategories. First is the Problem-solving concepts that got 14.65 %. This category includes subcategories of algorithm, mathematics/computational science and Artificial Intelligence. Second category is computer concepts(28.67%) that includes computer/hardware principles/architecture, inter-computer communication and operating systems. Next is the system/software concept which includes system architecture, software life cycle, programming languages, tools, product quality, human0computer interaction and system security. This category is only 19.11% used. The fourth is Data or information concept (15.45%) which includes Data/file, Data base/warehouse/mart organization, Information retrieval, Data analysis and Data security. After which is Problem-domain-specific concepts, Systems/software management concepts, Organizational concepts and societal concepts. These are some of the technical topics that computer science research usually addressed.

Next thing is the research technique being widely used in CS research. They have concluded that there are four major research approaches being used: the descriptive, developmental, formulative, and evaluative. The descriptive approach has three subcategories: descriptive-system (DS) that is used to capture papers whose primary focus is describing a system. The descriptive-other (DO) was added to capture those papers that used a descriptive approach for describing something other than a system, for example, an opinion piece. And the last one is descriptive-review (DR) as a subcategory into which we categorized papers whose primary content was a review of the literature. The formulative research approach was subcategorized into a rich set of possible entities being formulated, including processes/procedures/methods/algorithms.

Another point of the study is about the research method that describes the specific technique used in a given study. While the choice of research approach narrows the set of possible applicable research methods, there is typically a one-to-many relationship between a given research approach and method. Unlike research approach, where there were few candidate categories from which to choose, in the case of research method, there were numerous classifications from which to choose. Arguably, the computing discipline most concerned with research method is Information Systems where many prior publications have identified a number of commonly used methods. ). These articles identify, for example, laboratory experiments (using human subjects), field studies, case studies, and field experiment. Several other research methods have also been identified; for example, conceptual analysis (or conceptual study), literature review (Lai and Mahapatra, 1997), instrument development (Alavi and Carlson, 1992), and exploratory survey (Cheon et al., 1993). Some studies have examined research methods specific to a software engineering context. Both Zelkowitz and Wallace (1997) and Harrison and Wells (2000) proposed a number of research methods similar to those identified in the information systems studies cited above.

Next thing is the Level of analysis which refers to the notion that research work may be conducted at one or more of several levels; for example, at a high level, the research may be technical or behavioral in nature. Example of technical research would be focused on the computing system (CS), computing element (CE, representing a program, component, algorithm, or object) or abstract concept level. Some research work is done at the level of the profession (PRO), of which this paper is an example, as are those papers referenced in the introduction that address CS research in a particular country, while others may be conducted within an enterprise at the organizational (OC) level. The level of analysis in general are Society, Profession, External business context, Organizational context, Project, Group/team , Individual, Computing system , Computing element––program, component, algorithm and Abstract concept .

The last point is the reference discipline. By reference discipline, we mean any discipline outside the CS field that CS researchers have relied upon for theory and/or concepts. Generally, a reference discipline is one that provides an important basis, such as theory. ). Swanson and Ramiller (1993) identified computer science, management science, and cognitive science, organizational science, and economics as four key reference disciplines for information systems. Barki et al. (1988) also include behavioral science, organizational theory, management theory, language theories, artificial intelligence, ergonomics, political science, and psychology, while Westin et al. (1994) further identified mathematics/statistics and engineering.

The results from the study should be of value to both researchers and doctoral students engaged in computer science research. For example, this study provides a characterization of the types of articles that computer science journals publish. Researchers can use this knowledge to make choices when deciding on a target journal for their research. The results can also be used to provide insights into areas of CS research that are receiving little research attention. For example, in terms of research approaches, the results clearly suggest that insufficient emphasis is being placed on the use of evaluative methodologies. However, while the results clearly support Tichy et al._s (1995) claim regarding the lack of focus on evaluation in CS research, Fletcher (1995) cautions that the use of experimental methods may not always be appropriate in computer science, a caveat that should be kept in mind. Further, funding organizations such as NSF could use the findings of the research to provide focused calls for proposals aimed at fostering research in particular areas or using particular approaches/methods

Computer science is an extensive field of information technology. In this fast paced time, progressive researches on computer science are rampant. With regard to this, there are a variety of articles and information regarding computer science research, its state, its technical issues and concerns that various companies or organizations have notions and opinions with their individual activities and undertakings. One of it is the IBM’s Almaden Research Center.

The Computer Science group at IBM's Almaden Research Center leads the next generation of research in information-based computing, user productivity, healthcare IT and the theoretical foundations of computer science. They invent new algorithms and architectures for finding, integrating, managing, analyzing and protecting information, and explore and prototype new modes of user interaction. And also, they are creating the technical underpinnings for a national healthcare network and do fundamental research into game theory and mechanism design, lattices and the theory of semantic mappings. The innovations they have played a role in creating entirely new disciplines such as relational database management and have also led to novel research areas such as information mining, schema mapping, data disclosure management and activity management.

The said group explores these areas from theory to systems, and from the laboratory to practice. They apply their technology to problems faced by companies in a broad range of industries including finance, healthcare, telecommunications and retail, directly interacting with clients and leveraging IBM's unparalleled technical sales and services teams. They pursue a mix of medium- and long-term research, including high-risk/high-reward projects with the potential for disruptive and revolutionary business impact. They measure their success by their strong publication record and their impact on IBM’s business and the world. The IBM’s Almaden researchers are active and respected members of their scientific communities and collaborate with universities.

Another article is the summary report of Professor Krithi Ramamritham presented by the Office of Naval Research, Asian Office about Computer Science Research in India. It embarked on the matter of India’s state of research in computer science. Has India realized its potential for high-caliber computer science research? The summary paper addressed this question in the context of computer science. It stated that India has shown the potential for high-caliber computer-science research because of the basis that India's pool of technical man power is one of the largest in the world, the growth rate of India's software industry has been tremendous in the recent past, and the demand in the West for students from India's top science and technology educational institutions has been very strong.

Many computer science researchers in India have endeavored to carry out high caliber research in spite of limited infrastructure and resources to conduct and communicate their research. Many of the researchers are involved in collaborative activities with institutions abroad, primarily in the US. Given the untapped potential that exists, researchers abroad may find it profitable to seek collaborators within India to further their research goals.Indian computing industry must play its part, providing challenging opportunities that will bring out the potential in its employees. It cannot afford to sit on its current laurels for too long. The country needs technically-oriented leadership in the government to make this possible. Areas requiring attention include better incentives and appreciation for good research productivity, prudent management and use of research funding, enhanced salary levels for researchers at all ranks, appropriate means to set and demand accountability, and improved opportunities for peer interactions within India as well as for interactions between industry and academics.

In reference to the College of Engineering of NC State University, their key research areas are in Theory (Algorithms, Theory of Computation), Systems (Computer Architectures and Operating Systems, Embedded and Real-Time Systems, Parallel and Distributed Systems, Scientific and High Performance Computing), Artificial Intelligence (Intelligent Agents; Data-Mining, Information and Knowledge Discovery, Engineering and Management; eCommerce Technologies; Information Visualization, Graphics and Human-Computer Interaction), Networks (Networking and Performance Evaluation), Security (Software and Network Systems Security, Information Assurance, Privacy), Software Engineering (Requirements, Formal Methods, Reliability Engineering, Process and Methods, Programming Languages), and Computer-Based Education. The department has a number of teaching and research laboratories, centers and other facilities that support its educational and teaching mission.

Based on Wikipedia’s definition, Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. And there are different branches of computer science which are theory of computation, algorithms and data structures, programming languages and compilers, concurrent, parallel, and distributed systems, software engineering, computer architecture, communications and security, databases, artificial intelligence, computer graphics, and scientific computing. From these, we could derive the concept of the organizations of the state and their individual future undertakings in the field of computer science.

Based on the article “The Future of Computer Science Research in the US”, it was affirmed on May 12, 2005 at Washington, DC the Computing researchers informed a receptive congressional panel that the nation's dominant leadership position in information technology is at risk from cuts in research funding and changes in focus at federal mission agencies. The Computing Research Association, in written testimony endorsed by five other computing-related organizations, told the committee that the changing landscape for federal support of computing research threatens to derail the “extraordinarily productive” research enterprise that has enabled the innovation that drives the new economy.

The joint testimony notes a number of factors that imperil U.S. long-term leadership in IT, including DARPA's withdrawal from its historical support of university-based computer science research and cuts to the proposed IT research budgets at NIST, NASA, the Department of Energy and the National Institutes of Health."The impact of IT research on enabling of innovation resonates far beyond just the IT sector," said James D. Foley, Chair of CRA and professor of computer science at Georgia Institute of Technology. The computing research community testimony concluded with a call for the U.S. to maintain leadership in IT. "The U.S. still has the world's strongest capability in fundamental research in IT, and the most experience in how to leverage that capability towards economic growth," Foley said. But there are risks in letting uncertainty about funding that research linger.

Numerous conditions and situations of computer science in diverse organizations are varying in the researches’ extent of productivity and significance. As we look at their different states, we could run through that there are computer science researches that are ramping and mounting in investing and developing their researches while others are deteriorating and some are taking less consideration on its importance and advantage in the society.

The State of Computer Science Research in the U.S. and The Evolution of Federal Support for It

Statement of Wm. A. Wulf, Ph.D.President, National Academy of EngineeringandAT&T Professor of Engineering and Applied Science, University of Virginia before the House Science Committee U.S. House of Representatives

12 May 2005

First, in Science the Endless Frontier, the report that established our system of federal funding of basic research, Vannever Bush advocated a system in which the government funds research, but the research to be done is selected on its merit by the researchers themselves. He said that such a system would pay dividends to the nation in national security, prosperity, and health. It is hard to think of a better “poster child” for the truth of this assertion than Computer Science. Consider the abbreviated list:

All of these were made possible by the federal investment in long-term, basic computing research. It is a mistake to think of such funding as an “expense”; it is an investment that demonstrably has had a huge return! Technology such as that listed above is the return on the investments made a decade or more ago. Investments made today in research will have equally large returns for our children and grandchildren; conversely, it is our children and grandchildren that will pay if we do not make them now.

Second, computing and computer science is in the unusual position of being both a challenging intellectual discipline in itself, and providing an infrastructure for other fields of science, engineering, and commerce. While the benefits to society listed above can be directly attributed to computer science, there are also many more benefits that have resulted from the use of computing in everything from cosmology, to weather prediction, to health care, to Walmart’s “just in time” inventory. Across this broad spectrum, computer science has enabled a better quality of life for us all. For me this simply reinforces the notion that funds expended on computing research are demonstrably investment, not expense. They are, in fact, an investment with an enormous multiplier because advances in computing and information technology have immediate, direct and tangible benefits on virtually all human activities.

Third, I do not believe the “linear model” of technology development! In my experience, the idea that basic research begets applied research begets development begets benefits to society is both wrong and counter-productive when applied to public policy decisions! Instead, there is a marvelously rich and productive interplay between basic scientific discovery and application, between universities and industry, between societal need and technology. We refer to Figure 1 as the “tiretracks chart”; it shows the relation between industry and universities in the development of about twenty information technologies, each of which produces more than a billion dollars of revenue per year. As you can see, progress does not always start with basic research, and it often involves iteratively exchanging roles between university and industry. The bottom line, however, is that if federally-funded, university-based basic research weren’t “in the loop”, these enormously beneficial technologies would not exist. Basic research may not be the original source for all the benefits we enjoy from technology, but it is a vital and irreplaceable component of the rich system that produces them.

Fourth and finally, it’s about people, stupid! It is worth reminding ourselves that Bush’s Science The Endless Frontier was written in response to President Roosevelt’s question about how we can ensure that, if there were another world war, we would have the people able to do what scientists and engineers did to help win WW II. For all the bounties that we can point to as coming from computing research, the most important output has been the cadre of educated women and men that can take us to the next level. From personal experience, I firmly believe that the U.S. early dominance in electronics and software was because of the students educated by the enlightened policies of DARPA and NSF beginning in the 1960’s! If computing research has a large multiplier because of its broad application, then the people capable of doing that research are yet another multiplier on top of that! Disinvestment in university-based research is a disinvestment in the production of the next generation of people, with far greater negative impact than simply the loss of the research.

With that context, let me now turn to the three questions in your invitation to me:

1. What effects are shifts in federal support for computer science – e.g. shifts in the balance between short- and long-term research, shifts in roles of different agencies – having on academic and industrial computer science research? What effects are changes in the research likely to have on the future of the U.S. information technology industry and on innovation in the field?

2. Are the federal government’s current priorities related to computer science research appropriate? If not, how should they be changed?

3. What are [my] views on the recent President’s Information Technology Advisory Committee (PITAC) report on cybersecurity? What should the federal government be doing to implement the recommendations of this report? Should PITAC be renewed when its current term expires on June 1?

Although this hearing is about the state of computer science, I am concerned about what I perceive as a shift to more risk averse funding of research in all of the physical sciences and engineering, and in all of the agencies that have traditionally funded such research. At a macro-level, I am concerned that while this committee has authorized a doubling of the NSF budget, the funds have not been appropriated. I am equally concerned about the proposed decrease of DoD 6.1 funding. It is easy to make, and even to understand, the argument that in the current budget situation increases are not likely in either of these accounts; nonetheless, I find it deeply troubling that there seems to be little recognition of the long term consequences of a decision not to make these investments.

As I have testified to this committee before, it is not just that there is an increasingly short-term focus in some agencies, it is that even in those agencies with a longer term focus, when resources are tight, researchers themselves propose more incremental, less risky projects. Where bold new ideas are needed, as in cybersecurity, we see conservatism and temerity instead. There are exceptions of course, but perversely, when resources are tight we generally get less out of what we do spend. Someone once said that great research does not come from moments of great insight, but from moments of great courage! When the existence of one’s research program is on the line, courage becomes even rarer than usual. There is a cascading effect of this – more timid PI’s educate students to be more timid, provoking a long term decline in the quality of research.

With respect to computer science within this general drift towards conservatism, I would make several points:

First, at NSF the budget for Computer and Information Science and Engineering (CISE) has grown nicely from when I ran it in the late 80’s, and CISE is to be congratulated for using that growth to increase the average grant size rather than taking the politically easier route of funding more proposals. In addition, it has added center-scale projects through its Information Technology Research (ITR) program. Together, however, this has led to a potentially serious decline in the “success rate” in some areas – all though the success rate is determined by a number of factors and I do not have access to the data to let me analyze just how serious this is in specific areas. What I can say from discussions with my colleagues is that the computer science community believes that it is serious and has adapted its behavior accordingly: more time is spent writing proposals, more failed proposals are “recycled”, more incremental and less bold ideas are advanced, etc. I suspect that the decline in success rates is serious, but I know that even if it is not, it is having a significant negative impact.

NSF has, by the way, and with thanks to this committee, focused more resources on cybersecurity research. NSF is, in fact, now the major supporter of university-based research in this area. It is, however, also an example of the success rate problem mentioned above – only slightly more than 8% of the proposals in response to its Cyber Trust initiative were funded!

Second, I am deeply concerned about what has happened at DARPA. On top of a many year drift toward the less ambitious and more incremental, the Iraq war has been described as a reason to dramatically accelerate this – to focus on reaping the successes of the past, to focus on rapid development, to industrial development over university research, and to shift the balance strongly toward near term topics. While I can agree that reaping, developing and focusing on the near term are needed, so is long term investing. Without current investment there won’t be anything to reap next time.

The problem with trying to assess the consequences of the kind of shift we have seen at DARPA is that they are opportunity costs, measured in “might have beens”, and at best evident only years after the fact. By comparison with the tangible, immediate results of reaping and developing, such costs may appear ephemeral and perhaps even wasteful. Yet one can only wonder at what the world would be like today if the immediacy of the Viet Nam war had diverted ARPA from funding crazy ideas like networking, timesharing, VLSI, graphics, RISC architectures, RAID disk systems, parallel computing – or any number of other technologies that are essential to today’s computer industry and whose results pay off daily to industry, government and the consumer as well as the military.

Any number of studies have shown that it takes about fifteen years, plus or minus a few, for ideas to make their way from laboratory to product. One way to look at that is that there is a fifteen year pipeline of ideas and technology. Only a few of these ideas will, in fact, become commercial, and we have no good way to predict which of them will be the most important. Thus, if one stops filling the pipeline, the effect on industry will not be immediately visible as it “drains” the pipeline, nor will the exact nature of the future impact be predictable. But that there will be an impact is an inescapable lesson of history.

As was noted in the recent (February 2005) Defense Science Board (DSB) Task Force on High Performance Microchip Supply:

“University and independent laboratory work has played and important role in microelectronic history in that it has sown the seeds for major technological shifts. … At a time when the effectiveness of conventional approaches to the extension of Moore’s Law are nearing their end, new ideas are essential to continue the progress on which the industry and future military systems depend.”

Although this DSB report is focused on micro-electronics, much the same can be said for all aspects of information technology. At a time of growing global competition, DARPA’s disinvestment in university-based, long-term research is, in my view, a risky game for the country.

Third, please permit me to vent an old annoyance. Information technology has become critical to virtually every agency of the federal government, and specifically to those that fund research – NASA, DoE, NIH, EPA, NOAA, etc. I believe it is fair to say that these agencies could not fulfill their primary mission without the information technology developed in the last 50 years. Yet none of these agencies has contributed significantly to the development of the basics underlying that technology. As concerned and unhappy as I am with the trends at the traditional funders of computer science, I am at least as much so with the complete absence of those other agencies that benefit enormously from computer science research!

Now let me turn to the question about the government’s priorities. I suspect that the answer to this question by a set of randomly chosen computer scientists would vary enormously and correlate well with whether an individual researcher’s interest was on today’s “in list”. My concern is less with what is on today’s “in list” than with the frequency with which the list changes. As I tried to say in my previous testimony to this committee on the issue of cybersecurity, stability of funding is as important as its magnitude. Academic careers are built on a reputation for work done over decades. If the perception is that an area is a “fad”, it may attract a few weaker researchers, but the best researchers will migrate to where multi-decade support is probable.

I understand the desire for program officers and agency heads to “make their mark”, but I think the most effective and profound change the government could make would be to ensure that any new programs last long enough to have an effect – to attract people, let them find their footing, have a real chance to succeed or fail, and produce real benefit to society! Such a move would both raise the bar on evaluation of new programs and create the stability that will ensure that the best researchers become involved.

To answer your third question -- as you might expect from my previous testimony to this committee1, I am strongly in agreement with the recent PITAC report on Cybersecurity2. I am particularly pleased that they strongly identified the need for a better funded and stable program of long term basic research; as you will recall, that was what I also recommended. In my view, the dominant model of cybersecurity, namely a perimeter defense, is flawed and incremental patches to it will never result in the level of security we need for today’s systems, much less the increased dependence we should expect for future ones. This is an excellent example where boldness and courage are needed, and hence where the perception of excessively low proposal success rates can have severe consequences.

As I browsed pages on the Internet about the state of computer science research, I had landed on certain articles in various sites that tackle such topic.

By the way, one of the articles that I have read was all about the statement of Wm. A. Wulf, Ph.D, the president of the National Academy of Engineering and was on leave as an AT&T professor of Engineering and Applied Science of the University of Virginia that time. He presented it before the U.S. House of Representatives on the 12th day of May, 2005. He testified before the honorable about the state of Computer Science research in US.As to what I have understood about his statement, Wulf, first presented the Science in Endless Frontier, the report that launched their system of federal funding of basic researches. Vannever Bush promoted a system in which the government will support the research such as giving funds in order for the research to be possible. But it is sad to know that the research to be funded by the government is selected depending on how the researcher presented the good points of his research.

Upon the aforementioned system, I can say that the Computer Science researches in the United States are lucky enough even though researches to be funded by the government are selected only through how much the people can benefit by the research being proposed. Speaking of benefits, Wulf presented the kinds of benefits the research being selected should give. The dividends of the research are for the nation – for national security, prosperity and health. For the national security, he summed up the researches that have made possible. These are the smart bombs, GPS, unprecedented “information awareness” for war-fighter, unmanned robotic vehicles for surveillance, enormously enhanced training through the use of virtual reality. Among the benefits gained by the nation are the three percent of national productivity fueled by information technology, dozens of multi-million dollar of industries per year, internet-enabled business model, a forty-fold reduction on the cost of telephony, a global wireless phone system and many more. Among the researches that helped the field of health is the medical imagery such as CAT scans, cochlear implants, bio sensors, smart prosthetics, and smart defibrillating pacemaker.

Some may say that the researches of the technologies aforementioned are just a huge expense by the government, huge expense in a sense that the government prepares a huge amount of money in order to make the research possible. But as to what these technologies had imparted to the nation, these technologies returned huge investments to the nation. It may even return the investment twice or thrice depending on how beneficial these researches will make. Though some of the investment made by thee government take time to be returned, these will not be wasted because it will have equally large return fort he future generations.Secondly, Wulf also said that Computing and computer science is in the unusual position for being both a challenging intellectual discipline and at the same time it provides infrastructure in the other fields of science, engineering and commerce. Well, I guess, it is quite visible to what we, The CS research students are experiencing right now. To think it clearly, the topics being presented on the open forum last September 2 proved Wulf’s statement about Computing and Computer Science. As we can see, the proposed topics belong to computing. Engineering is also visible because the student/ researcher should plan for a framework of the project, must calculate necessary data if there are and things like that. Commerce; because all the topics presented can be manufactured for the use of the respective kinds of people the project is intended for. Research such as this made the quality of life to be better. With this, Wulf had justified that funding a research is not an expense but an investment. You can see the benefits after the research has been done and what you invest returns back to you.

“There is a marvelously rich and productive interplay between basic scientific discovery and applications, between universities and industries, between societal need and technology.” This is what Wulf believe rather than that of “basic research begets applied research begets development begets benefits to society”. I wish I had seen the figures he presented that time so that I can totally relate to what he is saying. Well, he pointed out a figure showing the relationship between industry and universities in the development of information technology which produces more that a billion dollars of revenue per year. With this, he pointed out that progress does not always start with basic research. It often involves iteratively exchanging roles between industry and university. However, if federally-funded, university basic research didn’t jive together, the technologies we are enjoying right now would not exist.

With Wulf’s statements above, I though that he is not pro to research, but as his following statement, he said that though basic research may not be the original source for the benefits that we are enjoying from technology, but it is the vital and irreplaceable component of the rich system that produces them.

Speaking about the state of Computer Science research, he pointed out that when resources are tight, researchers propose more incremental, less risky projects and that they get less on what they spend. In terms of funds, he cited that at NSF the budget for CISE (Computer and Information Science and Engineering) has grown nicely when it was in the late 80’s. A number of studies have shown but it takes years for these researches to make their way from laboratory to product. In fact, only a few of these ideas become commercial and there is no good way to predict which of these ideas will be the most important. Wulf also vent an old annoyance about agencies who gained a lot of benefits from information technology but does not even contribute to the development of the technologies to fulfill ther missions and yet Computer science research haven’t got any contribution from these agencies – NASA, DoE, NIH, etc.What is the variety of topics in Computer Science research?

Find any information/article and examine the state of computer science research and what are its variety of technical topics?

It is undeniably true that computer science or the field of computing technology has been rapidly growing in recent times. There are numerous development, inventions and discoveries that are introduced in the community today and I believe that this magnificent growth is the product of critical research from researchers in the said field. If we are to trace up history of computing science, development from abacus computers to digital frames are incredibly amazing! Who would expect that the technology would boom such as what we are enjoying right now. Can you Imagine computer science a decade after or even just a year from now as for the reality on how technology developed and even improved rapidly, hmm..?? (I wonder…). What is computer science by the way? It is defined that [1] computer science or computing science is the study and the science of the theoretical foundations of information and computation and their implementation and application in computer systems.

Based on an article written by Wm. A. Wulf Ph.D, the president of the National Academy of Engineering (AT&T Professor of Engineering and Applied Science, University of Virginia before the House Science Committee U.S. House of Representatives) entitled the state of computer science research in the US and the evolution of federal support for IT. On that article he exemplify[2] how important it is to support researches of computer science and it is very wrong to say that the estate where he belong would refer the funds being released to researches of computing science an expense but should or would rather be INVESTMENT. He added that computer science is an investment with an enormous multiplier because advances in computing and information technology have immediate, direct and tangible benefits on virtually all human activities. There is a contention concerning the issue "Investing" vs. "Expense”. He has pointed out that what the federal funding in basic computing research has contributed in the field of national security, prosperity and health is simply an "investment" and not an "expense". There is a distinction between the two; since "expense" sounds like valueless or basically it is just money spent on an activity while "investment means spending money "productively". These "investments" will reimburse themselves for the future generation. Computer Science research has brought vast contribution within the scope of physical sciences, engineering, commerce, cosmology and weather prediction. He has quoted that, "Basic research may not be the original source for all the benefits we enjoy from technology, but it is a vital and irreplaceable component of the rich system that produces them".

After reading the article of Mr. Wulf, where he greatly emphasized that supporting the researches on computer science must not be considered as an expense but rather be an investment, I felt so proud that I took this course Bachelor of Science in Computer Science because if we try to think of it, my contribution in the near future would somehow maybe help the development of this country and I myself will not be a liability for this country but rather be an asset (Patriotic statement). Now, going back to Mr. Wulf, I strongly agree with his statement, many of the highly industrialized and developed countries today (Japan, United States, and Singapore) had invested and focused on technology development. Well, of course, if one country aims for success and growth, one must have to released funds and take the risk to be able to gain something and it is proven true that investing on technological development is one of the key factors for economic growth and development. Honestly, Mr. Wulfs’ heart and dedication towards promoting undying support to computer science research is very admiring and inspiring. Philippines in particular, as what I have observed is not that supportive on computer science researches. It is very transparent that the government is not paying that much attention on improving and developing the quality of educating the students or orienting them with the newest technology, and encouraging them to do more research, knowing the fact that our country is competing globally. With regards to the researches, it is pretty obvious that there are lots of Filipino computer scientist which are magnificently very good but then are not being supported properly that is why they flew away and try to find that green pasture outside the country. Well, aside from the fact that lots of researches, inventions and developments with regards to technology are first released and broadcast by non-Filipino developers (sad to say).

There are varieties of technical topics involve in computer science research, some of which are:

Through various Computer Science researches done in the different parts of the world, the quality of life of every individual gained immense improvement for the past centuries. It greatly affects the environment and the people living on it. Technology we all have today is the result of man’s continuous and never-ending search for new ideas that could be the solution of every single problem we usually encounter in our daily living.

The question now would be what is the current state or situation of Computer Science research?

According to Chris Johnson, a Computing Science Professor in Glasgow University, in his paper states the expanding scope of `computing science' makes it difficult to sustain traditional scientific and engineering models of research. In particular, recent work in formal methods has abandoned the traditional empirical methods. Similarly, research in requirements engineering and human computer interaction has challenged the proponents of formal methods. These tensions stem from the fact that `Computing Science' is a misnoma. Topics that are currently considered part of the discipline of computing science are technology rather than theory driven. This creates problems if academic departments are to impose scientific criteria during the assessment of PhDs. Computing science is an immature discipline. Vast resources have also been poured into the subject in a relatively short period of time. This has brought startling advances in both hardware and software engineering. Unfortunately the development of computing technology has not been matched by a similar development in academic research techniques. In the pursuit of technological goals, researchers have borrowed models of argument and discourse from disciplines as varied as philosophy, sociology and the natural sciences. This lack of any agreed research framework reflects the strength and vitality of computing science.

Chris Johnson stated that because of the increasing range of Computing Science, recent researches done in computer/computing science has left the formal methods of traditional experimental methods making it harder to maintain the traditional scientific and engineering models of research. Most research topics considered in computing science are technology such as new innovations rather than theory driven.

I also read the article entitled, The State of Computer Science Research in the U.S.and The Evolution of Federal Support for IT wherein Wm. A. Wulf, Ph.D., President, National Academy of Engineering and AT&T Professor of Engineering and Applied Science, University of Virginia, addressing on House Science Committee, U.S. House of Representatives, stated his four points of view concerning the computer science research.

First, in Science the Endless Frontier, the report that established our system of federal funding of basic research, Vannever Bush advocated a system in which the government funds research, but the research to be done is selected on its merit by the researchers themselves. He said that such a system would pay dividends to the nation in national security, prosperity, and health. It is hard to think of a better “poster child” for the truth of this assertion than Computer Science. Consider the abbreviated list:

All of these were made possible by the federal investment in long-term, basic computing research. It is a mistake to think of such funding as an “expense”; it is an investment that demonstrably has had a huge return! Technology such as that listed above is the return on the investments made a decade or more ago. Investments made today in research will have equally large returns for our children and grandchildren; conversely, it is our children and grandchildren that will pay if we do not make them now.

Second, computing and computer science is in the unusual position of being both a challenging intellectual discipline in itself, and providing an infrastructure for other fields of science, engineering, and commerce. While the benefits to society listed above can be directly attributed to computer science, there are also many more benefits that have resulted from the use of computing in everything from cosmology, to weather prediction, to health care, to Walmart’s “just in time” inventory. Across this broad spectrum, computer science has enabled a better quality of life for us all. For me this simply reinforces the notion that funds expended on computing research are demonstrably investment, not expense. They are, in fact, an investment with an enormous multiplier because advances in computing and information technology have immediate, direct and tangible benefits on virtually all human activities.

Third, I do not believe the “linear model” of technology development! In my experience, the idea that basic research begets applied research begets development begets benefits to society is both wrong and counter-productive when applied to public policy decisions! Instead, there is a marvelously rich and productive interplay between basic scientific discovery and application, between universities and industry, between societal need and technology. We refer to Figure 1 as the “tiretracks chart”; it shows the relation between industry and universities in the development of about twenty information technologies, each of which produces more than a billion dollars of revenue per year. As you can see, progress does not always start with basic research, and it often involves iteratively exchanging roles between university and industry. The bottom line, however, is that if federally-funded, university-based basic research weren’t “in the loop”, these enormously beneficial technologies would not exist. Basic research may not be the original source for all the benefits we enjoy from technology, but it is a vital and irreplaceable component of the rich system that produces them.

Fourth and finally, it’s about people, stupid! It is worth reminding ourselves that Bush’s Science The Endless Frontier was written in response to President Roosevelt’s question about how we can ensure that, if there were another world war, we would have the people able to do what scientists and engineers did to help win WW II. For all the bounties that we can point to as coming from computing research, the most important output has been the cadre of educated women and men that can take us to the next level. From personal experience, I firmly believe that the U.S. early dominance in electronics and software was because of the students educated by the enlightened policies of DARPA and NSF beginning in the 1960’s! If computing research has a large multiplier because of its broad application, then the people capable of doing that research are yet another multiplier on top of that! Disinvestment in university-based research is a disinvestment in the production of the next generation of people, with far greater negative impact than simply the loss of the research.

These are some areas of Computer Science where technical research topics can be done:

Find any information/article and examine the state of computer science research and what are its variety of technical topics?

We can find information with regards to computer science and their variety in many articles and organizations. This applies the use of technology. The example below is a university that focused on how to introduce to their students the appropriate knowledge of computer science. In the Department of Computer Science at Florida State University their mission is twofold. One goal is to provide students with the fundamental knowledge and problem-solving skills in Computer Science required for a fulfilling career. The other goal is to create and disseminate knowledge to improve computer science research, education, and practice.They have a vibrant and growing department that has changed substantially in recent years in many ways. The number of faculty has significantly increased in the last 15 years and the department now has 20 faculty members. Their department offers a bachelor's degree in CS, three tracks for the master's degree in CS, and continues to offer the PhD degree in CS as well. Through a joint effort between the FSU Biology and Computer Science departments, FSU is now one of the few universities in the country offering a bachelor's degree in Computational Biology. They also have created an interdisciplinary bachelor's degree in Computer Criminology by working with the College of Criminology and Criminal Justice. Their research funding and the number of research assistants has significantly increased in recent years. Many of their faculty are internationally recognized, hold distinguished positions on editorial boards and conference committees, and with their students are publishing innovative research in very prestigious conferences and journals.Also they encourage people to explore their department through their web pages or in person. People will find both faculty and students who are striving for excellence in both Computer Science education and research.The 2003 National Science Foundation (NSF) report, Revolutionizing Science and Engineering through Cyber infrastructure, provided critical documentation of the challenges and opportunities of e-research. It proposed to “use cyber infrastructure to build more ubiquitous, comprehensive digital environments that become interactive and functionally complete for research communities in terms of people, data, information, tools, and instruments that operate at unprecedented levels of computational, storage, and data transfer capacity.” Further, the NSF report noted that the emerging e-science projects “require effective federation of both distributed resources (data and facilities) and distributed, multidisciplinary expertise, and that cyber infrastructure is a key to making this possible.” Libraries have potential roles to play in both the development of the technology and organizational infrastructure. A more recent NSF report, Cyber infrastructure Vision for 21st Century Discovery, lays out amore detailed plan of action (NSF 2007). Four interdependent areas of investment are specified: •High-Performance Computing: investments in pet scale capabilities for science and engineering. •Data, Data Analysis, and Visualization: investments in data/metadata/ontologies, data collections, and the development of a national digital data framework. •Virtual Organizations for Distributed Communities: investments in tools and technology systems for collaboration as well as evaluative research on the social and organizational dimensions of virtual communities. •Learning and Workforce Development: investments to prepare professionals who willA case can be made that research libraries already have existing capacity and expertise that they can bring to bear to support e-science. By virtue of their experience in service and data management, and, for many, their mission, they are capable of advising and developing infrastructure to support the needs of scientists working in a cyber infrastructure-enabled environment. For example, research libraries have: •Expert understanding of the policies and principles related to open exchange of scholarly information, as well as the roles that can be played by institutional repositories in assuring that exchange, and a demonstrated ability to offer and support both institutional repositories and domain repositories (e.g., arXiv) •Experience with developing and supporting integration and interoperability tools for information distribution and discovery, both within and across disciplines (e.g., SFX, metasearch, metadata standards, SIMILE) •Experience with developing and supporting both business and technical strategies for long-term archiving (e.g., archival support generally, Portico, grant research with NARA,NDIIPP) •Understanding of archival and life-cycle aspects of scientific information, including the importance of assuring access and usability over the long term (preservation, metadataThese are the Technical Topics in which Computer Science Researches are now focused:

In creating a research, there are two kinds of it. One is for social research and the other is for technical research. Social research refers to research conducted by social scientists (primarily within sociology and social psychology), but also within other disciplines such as social policy, human geography, political science, social anthropology and education. Sociologists and other social scientists study diverse things: from census data on hundreds of thousands of human beings, through the in-depth analysis of the life of a single important person to monitoring what is happening on a street today - or what was happening a few hundred years ago. While on the other half, technical research is an applied research oriented toward engineering disciplines (but not to a specific product or process) and aimed at developing tools and test equipment and procedures, and at providing solutions to specific technical problems.

The question really is about what the state of computer science research is and what the varieties are of technical topics. From the first question, I have read an article titled Computer Science in India. And on how the researches have been a big help in India's technological and economic progress. Computer Science (CS) research in India started in earnest only in the mid-80 triggered by the establishment of post-graduate programs in many institutions throughout the country at that time. Today, almost all areas of computer science research are covered by researchers in India, including topics that are "hot" elsewhere such as multi-media, workflow automation, virtual reality, and hardware-software co-design he territory covered by Indian researchers is impressive and most of the research problems tackled are of current interest globally. Some of the research has even attracted international attention including work on neuro-fuzzy systems, machine learning, genetic and neural algorithms, the modeling and control of flexible manufacturing systems, speech synthesis, databases, and complexity theory. One area where solutions unique to Indian conditions have been developed is machine-assisted language processing. With a vast population conversing in a multitude of languages (there are over twenty officially-recognized regional languages!), many with their own scripts, the problem of translation and transliteration from English to these languages and from one Indian language to another is daunting, but one which has the potential for a huge pay-off, -- socially, politically, and economically. It is not surprising that many computer science researchers are grappling with this problem. Some of the solutions are quite mature, and available as commercial software offerings. Many of these permit interactions with the computer in a local language, using keyboards designed explicitly for the language.

The results of the efforts mentioned above demonstrate that it is possible to carry out high-quality research in India, leading to publications in visible international journals; the potential exists and the resources can be garnered. However, most of the rest of the research is found wanting in quality. Incremental solutions -- developed relative to an existing published result, and the lack of in-depth evaluations -- are the norm. A senior faculty member at an IIT summarized the status of computer science research at India's leading basic research institutions thus: "The averages are there, but the peaks are not."

Several explanations can be offered for this gap between potential and reality. They relate to an ill-defined definition of the purpose of research in a developing country like India, absence of incentives as well as recognition, lack of critical mass in most research areas, paucity of resources -- both in quality and quantity, suboptimal utilization of what is available, low funding levels and the missing of accountability.

There are many in Indian computer science who argues that the goals of research and development in India ought to be manpower development, increasing competence, and keeping faculty up-to-date with current techniques. Towards this end, it is said that "reinventing the wheel" is not only necessary but also important. This might be one of the reasons that even though it is said (repeatedly) that India has one of the world's largest technical manpower, the manpower needed to do state-of-the-art research is found to be wanting, both in quality and quantity. According to Prof. Mahabala of Indian Institute of Technology (IIT) Madras, this is because the "driving forces are not here." Since highly-trained, quality manpower is the key to the founding of new enterprises and for entering novel highly value-added arenas, many policy makers appear concerned with this issue. It is high time, since many echo Prof. Narasimhan, a doyen of Indian computer science, who feels that "there is no systematic effort to break new ground" even though information technology is more available now.

A stumbling block is the prevalent view that it is difficult to do "cutting-edge" research in India. A related view is that "creating new areas is very difficult, but contribution to an existing area is possible". A researcher who recently returned to India from the U.S. said that, because of this, one needs to come equipped with broad-based interests rather than a narrow focus. (As it turns out, whereas for almost twenty years research organizations had a difficult time attracting Indian researchers working abroad, the last few years have begun to see a reversal in this trend.)Because of the breadth of research coverage, in most areas of computer science research there is a subcritical research force as a result of which most Indian researchers work in isolation. They hence miss the much-needed opportunity to interact with peers and fellow workers in their area of specialization. Even when there are related efforts elsewhere within the country, as a researcher admitted, "Indians don't know what others are doing." With the current availability of e-mail, a few researchers have begun collaborative efforts, mainly with colleagues overseas. Many are of the opinion that cooperation among researchers within India will not pick-up substantially due to the limited monetary resources available and the severe internal competition that it implies. One of the fall-outs of the subcritical research mass has been the inability of the funding agencies to obtain quality peer reviews. One area that does not suffer from this problem is computer science theory. Most research-oriented academic departments have a substantial theory group, often the only group with critical mass. These researchers do not have to contend with the lack of resources and many with mathematical background find it an easier area to (re)train themselves in.

Besides a few research groups, ones with the required critical mass, very few researchers work with long-term research goals -- needed to have a coherent vision -- and strive to achieve it. This, along with an apparent lack of recognition of "sparks", a problem mentioned by many junior faculty, are cited as two of the many reasons for lower visibility of Indian computer science research. Another reason given is the paucity of research funds and the manner in which it is administered. This research study in India has been funded along the way in order to create a blastful research. This kind of study is not only for the Indian alone, but as well to the community all over the world. This is one of the bases that the creation of this research is a proof that computer science research is growing. But on the other half, the creation of this article is basically one of the factors that Indian community is more likely coming to full.

Computer science (or computing science) is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe and transform information. According to Peter J. Denning, the fundamental question underlying computer science is, "What can be (efficiently) automated?" Computer science has many sub-fields; some, such as computer graphics, emphasize the computation of specific results, while others, such as computational complexity theory, study the properties of computational problems. Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing computations, while computer programming applies specific programming languages to solve specific computational problems, and human-computer interaction focuses on the challenges in making computers and computations useful, usable, and universally accessible to people. The general public sometimes confuses computer science with vocational areas that deal with computers (such as information technology), or think that it relates to their own experience of computers, which typically involves activities such as gaming, web-browsing, and word-processing. However, the focus of computer science is more on understanding the properties of the programs used to implement software such as games and web-browsers, and using that understanding to create new programs or improve existing ones.

I have read an article about computer science research which tackles about robotics. The title of the research article is the Role of Simulation in Robotics by Richard Szabo. Robots, until recent years hearing this word we could think about only one type of existing application: industrial multi-joint systems working at assembly lines, welding car components, or sorting soda cans. The most important task of these automats is the reliable, long term work. However there is a serious gap between the majority of current robots and our expectations about robots. Autonomous arms work in an artificially created, predetermined, static environment where planning can be carried out. Freshly designed mobile robots like lawnmowers wander between electric wires, while owners of automatic vacuum cleaners place deflector walls and remove unneeded objects from the ground to facilitate cleaning. In contrast to the actual possibilities future robots must work in a continuously changing, fairly complex world, far from these aseptic conditions. It also means they have to create a more viable, human-friendly, or at least more elaborated world model to be successful. The problem is extremely hard. The results of early artificial intelligence like automatic theorem proving, checker programs, packing bulding blocks in microworlds, in spite of unexpectedly fast and obvious successes, could not yield a major breakthrough in solving less abstract tasks outside the computer with no preprocessed information. One aspect of difficulties turns up from the fact that receptors do not deliver direct, human recognizable description of the world, that is they do not generate On(Glass, Table)-like logic expressions, but transport various sets of digital signals to decisioning modules. The essence of the refinement of our genetically pre-wired perceptional and motional mechanisms does not strike the eye. We can hardly perceive our blind spot, what our vision almost totally compensates. We do not crack up a drinking-glass or let it fall to the ground correcting the holding force continuously and unconsciously. Substantial part of human brain capacity deals with perception and motor control. This kind of intelligent input and output is not given to robots; it has to be created by researchers. What humans and robots are common that their perception and action both err? The applied instruments have finite resolution; they are subject to failure and malfunction, which makes planning more troublesome.

This article is a research paper that examines the role of simulation in robotics. Simulation is the imitation of some real thing, state of affairs, or process. The act of simulating something generally entails representing certain key characteristics or behaviours of a selected physical or abstract system. Simulation is used in many contexts, including the modeling of natural systems or human systems in order to gain insight into their functioning. Other contexts include simulation of technology for performance optimization, safety engineering, testing, training and education. Simulation can be used to show the eventual real effects of alternative conditions and courses of action.What I have observed on the state of computer science research based on the article that I had found was that considering that the type of research is computer science it is expected that research will be dealing more about the technology and other innovations or let us say more about related topics on computers. In the article taken form generation5 which is entitled " The role of simulation in robotics", the writer of the article state the beginning of robots and other existing application on many years ago and its capacity. Some pictures are also provided so that we easily differentiate the before and the after. Some facts are also presented as addition to prove that it is really true. An introduction of Information all about Robots should be also there. Since this article doesn't focuses only in robots but also in simulation, there is also some discussion about it. As I understand that simulation is like role-playing or imitating, the writer compares it to a reality so that we can more understand the difference of the two or its significance. A backward draw of simulation and the advantages of it, of course reference should be there. What I stated here is based on the article i have found. There are more different ways on how the state of computer science research based on the article constructed.

Basically, the state of computer science research is growing. Since I have simulation subject only this year, this is new. It uses model and as well as modeling. Then again, in simulating robotics, it is indeed doing projects with models. Again, based on what I have read about this article, it is defining what simulation would help for robotics or creating robotics system. Definitely, again, state of research is growing. The discussion also asked about the technical topics found in computer science research. And listed below are the examples:

Social research refers to research conducted by social scientists (primarily within sociology and social psychology), but also within other disciplines such as social policy, human geography, political science, social anthropology and education. Sociologists and other social scientists study diverse things: from census data on hundreds of thousands of human beings, through the in-depth analysis of the life of a single important person to monitoring what is happening on a street today - or what was happening a few hundred years ago. Technical research is an applied research oriented toward engineering disciplines (but not to a specific product or process) and aimed at developing tools and test equipment and procedures, and at providing solutions to specific technical problems. But since the question is the state of computer science research is involved, the technical research is applied to this. Computer science research involves computation, citation, graphics, and simulation.

Computer Science Research in Mexico, is the title of the article I have read. Particularly worthy of note is the philosophy of looking ahead by investing in computer science research, though the vicissitudes of governmental focus and funding can still leave the field in a precarious position. In Mexico, as throughout the world, the need for computer capability outpaces the supply of qualified computer science professionals. Computer science is not a field that can be ignored.

CONACyT (National Council of Science and Technology) is the counterpart of NSF in Mexico, providing funding for all areas of science and technology. The top public universities, IPN (National Polytechnic Institute) and UNAM (National Autonomous University of Mexico), receive operational funding from the federal government. Salaries are low, about U.S. $28,000 annually, and faculty teach one to two courses per semester. Tuition for students is quite low. When UNAM recently proposed an increase from $0.02 to $145 per year, students protested with a loud and lengthy strike. IPN recently founded a new research center that has grown rapidly with special institutional support for better salaries via research grants from CONACyT. Some scientists from Russia and Cuba are participating in this effort. The top private universities for research are ITESM (Institute of Technology and Higher Studies of Monterrey: Monterrey, Morelos, and State of Mexico campuses) and UDLA (University of the Americas: Puebla campus).

Private universities are funded through foundations, usually supplemented with resources from industry and tuition. Until recently, due to Mexico's egalitarian attitudes with regard to public monies, private institutions were unable to receive government research support. Salaries are about U.S. $36,000 annually, and faculty teach 3 courses per semester. Separate from universities, the Mexican federal government invests in a number of public scientific research institutes, several with international reputations. A board and a director oversee each center and choose areas of research to pursue within funding allocations. In the area of computing, CIMAT (Center for Investigation in Mathematics) specializes in image processing, CICSE (Center for Scientific Investigation and Higher Education of Ensenada) focuses on software engineering and cluster programming, and INAOE (National Institute of Astrophysics, Optics and Electronics) works in computer control. There is one independent computing research institute in Mexico. In 1991 a group of UNAM faculty established LANIA (National Laboratory of Advanced Computer Science) so that they could pursue research in theoretical artificial intelligence, including multi-agent systems and logic.

With additional funding opportunities and government requests, LANIA has grown and now includes research in the areas of image processing and computer vision, programming languages and methodologies, distributed and cooperative computing, general IT consulting, human resources training, and direct government support such as computer network installation. Almost all research in computing is done in these academic institutions and research centers. Industry has made some efforts to establish research facilities, but the lack of qualified researchers has hampered their efforts. Through 2000, approximately 160 Ph.D. computer scientists were working in Mexico; most received their degrees from universities in the United States, France, England, Japan, and Spain. In recent years, ITESM, UNAM, UDLA-P, and IPN have established Ph.D. programs.

Since that this research involves computation and other things that a computer science have, this study also have funding institution that may, can or will help in implementing the study. REDII (Network for Development and Investigation in Informatics) was established by CONACyT in 1998 with the goal of transforming computer science research and education within Mexico. Recognizing that Mexico cannot build a research capacity in computer science without also developing the people who are going to do the research--and knowing that in a developing country pure research must be balanced with an emphasis on practical development--REDII had a dual intent: to simultaneously fund interesting, useful research, while also supporting the future generation of researchers. REDII funded both public and private institutions, not individuals.

The institutions then supported projects or general development, but the monies could not be used for salary or release time. REDII was unique in that it was set up to directly fund research in computer science, not the panoply of scientific disciplines within Mexico. And, proposals were reviewed by CS research scientists. Of the nine institutions and more than 40 projects currently funded, two examples are Enciclomedia and Phronesis.

This research article is a continuation of research in theoretical artificial intelligence, including multi-agent systems and logic. And since that the research study in Mexico have done before, hence, I therefore say that the research study in the area is uplifting to the next level.

Office of Naval Research, Asian OfficeComputer Science Research in IndiaA summary report by Prof. Krithi RamamrithamAccording to Ramamritham (1995), India has shown the potential for high-caliber computer-science research. He stated some facts and here are the following:· India's pool of technical man power is one of the largest in the world, · The growth rate of India's software industry has been tremendous in the recent past, and · The demand in the West for students from India's top science and technology educational institutions has been very strong. The report was all about the Computer Science Research in India, in which the first discussion would focus on the Nature of the Computer Science Research in India, then it is followed by the kinds of organizations in which the said computer science research is conducted then followed by the support for conducting research in the form of equipment, infrastructure and publications is then discussed. It has been said that India is the sought after IT Professionals, they are not just proficient in English but also with their works. Today, almost all areas of computer science research are covered by researchers in India, including topics that are "hot" elsewhere such as multi-media, workflow automation, virtual reality, and hardware-software co-design. In addition, some of the research has even attracted international attention including work on neuro-fuzzy systems, machine learning, genetic and neural algorithms, the modeling and control of flexible manufacturing systems, speech synthesis, databases, and complexity theory. But what really caught my attention is that Indians were able to develop a solution to cope up with the conditions in conversation of multitude of languages. It means that Indians have developed a machine-assisted language processing. As we all know, not everyone can really speak English fluently but then with the help of the technology that was built by the Indians that would truly help not just their fellow men but also every citizen in the world. Of course, the technology that was developed go through extensive research. And with these developed technology, that would just simply prove that Indians do produce high quality and very good research.One thing I have also liked about is that, in India, there are 3 categories of institutions that conduct Computer Science Research in India. And these are the following:· The first one is the six major research and teaching institutes devoted to science and technology. The following are taken from the article. These six institutes are the IITs (of which there are five, with one more coming up in Assam) and IISc, located in Bangalore. These institutions form a select group in the minds of the government as well as the citizens. The next tier of institutions is made up primarily of the Regional Engineering Colleges (RECs), with one located in each state. Also, there are several other universities where computer science research is being conducted quietly. (One such is the University of Hyderabad; researchers here are very active in (collaborative) AI research, keeping close contacts with overseas colleagues.) But a considerable gap does exist between the six top tier institutions and the next because of high teaching load imposed on the faculty, students being, on average, of a lower quality, and finally poorer infrastructure, namely library and computing facilities. · Government-Sponsored Institutions There are organizations in India that are funded and supported by their government and different ministries and departments. These are just some of the examples:o TIFR and the Institute for Mathematical Sciences (MatScience) perform research which is predominantly of a theoretical nature. These are funded by DAE. o Defence-related work takes place in a number of labs around the country, many located in Bangalore and Hyderabad, both in Southern India. A good example is CAIR which can be described as a "think- tank" serving the AI and robotics needs of Indian Ministry of Defense. It is a component of the Defense Research and Development Organization (DRDO).o The Ministry of Planning funds ISI, with its primary location in Calcutta. (It is worth noting that the first indigenous digital computer -- fabricated using discrete transistor units -- was commissioned by ISI in 1966 in collaboration with Jadavpur University.) o NCST also carries out research in several areas of computer science besides having education and training among its functions. NCST is a successor of the erstwhile National Center for Software Development and Computing Techniques (NCSDCT) which was a component of TIFR. o The Indian Space Research Organization (ISRO), is also involved in computer science work, but most of its work is of an applied nature, in the context of satellites and launch vehicles. ISRO has been building satellites for remote sensing as well as for communication. Its most recent success involved the launch of the Polar Synchronous Launch Vehicle capable of launching 1000-Kg class satellites into sun-synchronous orbits. o National Aerospace Laboratories (NAL), Bhabha Atomic Research Center (BARC), and Center for the Development of Advanced Computation (CDAC) have had the development of parallel processing platforms for solving computational science problems as the main focus of their computer science research. How I wish that our country would have one like that. Even just a little support from the government in conducting Computer Science Research and not just depending on outside funding institutions. It may be sad to admit but other countries offer support to our fellow men to conduct research but the Government itself cannot support its own people. One thing is for sure, the issue is really not about money, our country is rich but then with the officials that are in the position do not know how to value Research as much as other countries do. But then, based on the recent State of the Nation Address of the President, she would like to come up with a Department of Information, Communications and Technology. I just hope that this one would push through since having this department; we would have the chance to do research and seek help to the government via this department. And not just that, this would give opportunity to IT Professionals to excel and be heard in the country.

Computer science is a well-established discipline that is represented in almost all institutions of higher education. As part of their faculty responsibilities, computer scientists conduct research in several different areas, such as artificial intelligence, databases, distributed systems, etc. Research is published in journals dedicated to fostering research in those specific areas. Most of the papers that examine the nature of research within Computer science tend to focus on specific areas or even sub areas or data modeling rather than on the discipline as a whole.

Computer Science Research gives you the knowledge you need thus creating a path for a career in the topic you have chosen to focus. When you choose a topic, you are engaged in all the related or necessary research to pursue on your own. If you are able to think or be in the position of a researcher specializing in the computer science technology, you will gain a lot of significant benefits that will help and improve your career.

According to V. Ramesh, Robert Glass and Iris Vessey on their study entitled Research in Computer Science: An empirical Study, Computer Science examines a variety of technical topics it is relatively focused in terms of the level at which research is conducted as well as the research techniques used. Further, Computer Science research often relies on the job outside the discipline for its theoretical foundations. They present their findings as an evaluation of the state of current research and as groundwork for future Computer Science research efforts. There primary concern is to know, first, the topics that a computer science research is address, identify the approaches being used in implementing a CS research, discover the methods that was used by the researchers, the reference discipline and lastly the level of analysis.

Computer Science Research is evenly divided across five major topic areas: problem-solving concepts, computer concepts, systems/software concepts, data/information concepts and problem-domain-specific concepts. The researchers provide a table that shows the percentage of every major topic areas. The leading category is the computer concepts which include computer or hardware, architectures or principles, inter-computer communication (networks, distributed systems) and operating system. Problem-domain-specific concepts are the second on the rank which consists of its subcategories such as scientific or engineering, information systems (including decision support, group support systems and expert systems), systems programming, computer graphics and pattern analysis. Followed by systems/software concepts and part of it are the system security and architecture, system engineering, programming languages, methods or techniques, tools, product quality and human-computer interaction. Next is the data or information concept. With this concept, data structures, file structures, data base/warehouse/mart organization, data analysis and data security are attached to it. And lastly is the problem-solving concept that got the lowest percentage on the list. Problem-solving concept consists of subcategories of algorithm, mathematics or computational science, methodologies (object, function/process, information/data, event, business rules) and the artificial intelligence. Other things that can be considered in findings for computing topics are the organizational concepts, social concepts and disciplinary issues. In Organizational concepts a part of it are the organizational structure, strategy, alignment, organizational learning, knowledge management, technology transfer, information technology implementation, IT impact, Management of computing function, information technology usage/operation, and the legal, ethical, cultural and political implications in an organization. With social concepts, it includes cultural, legal, ethical, political implications. And the last one, the disciplinary issues. Part of it is the computing research and computing curriculum or teaching.

The next thing that they examine is the different approaches in conducting a computer science research. It has a subcategory with a multifaceted subcategory that be made up of formulating processes, procedures, methods, or algorithms. There are three types of research approach: Descriptive, Evaluative and Formulative. After evaluating which is the most important research approach they conclude that the focus of most areas of computer science research is more on formulating things.

They then identify the methods mostly used by the computer science research. According to their presented survey, the conceptual Analysis/Mathematical was the primary research method with conceptual analysis (does not use mathematical techniques.)There are many kinds of methods in computer science research such as action research, conceptual analysis, case study, data analysis, field study, mathematical proof, literature review/analysis, simulation, concept implementation and etc. After finding the research method is configure the level of analysis.

Aside from the research approach and research method, the levels of analysis were also one of the focused of a computer science research. It consists of subcategories which are computing element (relates to algorithms, methods and techniques), and abstract concept (relates to the definition of global predicates in the framework of distributed computations).In finding for level of analysis, it could be profession, individual, computing system or an abstract concept.

In the reference of discipline, from the reference disciplines used by the researchers, you will see that mostly a computer science research does not rely on the other fields for its fundamental theories and/or concepts for the reason that computer science was already considered a reference discipline itself. The reference discipline has its subcategories such us cognitive psychology, computer science, science, mathematics, engineering, economics, library science, management, public administration and public science.

In this empirical study of the researchers, they sought to evaluate the characteristics of a computer science research. The researcher used the classification system to record the keywords that describe their study. Their study is classified as follows: the topic is computing research; their research approach is an Evaluative-Other (EO) since their paper is more on evaluating and analyzing a computer science research; with their research method they used a literature review or analysis; profession (PRO is used in finding their level of analysis); however, they don’t have a reference discipline because they did not use any concepts from other disciplines in performing and implementing the study.

This output of the empirical study of the researchers reflects the environment of computer science research considering that it is a representative of the field. There study gives the classification of the different types of articles that computer science journals published. Given those different concepts and categories, researchers can use this additional knowledge in making choices or deciding a journal for their research.

University Mission Statement on Research"As a university, Xavier pursues truth and excellence in teaching, research and service to communities: it is concerned with the preservation of the environment and the integrity of creation; it prepares men and women with competence, skills and keen sense of responsibility to their communities ..."College of Engineering Mission Statement on Research"As a resource center, it shall establish a science and technology research center, develop information technology and serve as a forum for dialogues on technology and social impact"Mission Statement"As teaching, research and service unit, it shall conduct applied research in computer science to develop and adapt new methods and improve on existing solutions for harnessing information and communication technologies in the service of the community"General ObjectivesThe department shall conduct research in the areas of databases and information systems; multimedia and computer-aided learning systems; networks and computer systems; and programming and software engineering systems:ท To establish a system for investigating new ways of harnessing information and communication technologies in the service of the community;ท To take the lead in developing computer-based alternative and interactive methods of learning and learning management;ท To put in place a mechanism for responding to the rapid pace of technological change and the systematic updating of the computer science curriculum and syllabi;ท To encourage and provide incentive to faculty and students to pursue research in collaboration with academe, industry and government.

Units of Study• Each area of computer science chooses different units of study.– In algorithms: algorithms– In AI: methods, techniques, algorithms– In Languages: languages, language components or features– In Architecture: instruction sets, memory hierarchies, architectures– In Theory: models, theorems, proof techniques– In Systems: systems, components of systems, system architectures

Major Research Areas/Groups1. Information Systems and Data Management Group The Information Systems and Data Management Group is to develop new solutions to local problems in the integrated management and retrieval of data, information and knowledge in highly distributed networked environments in academe, industry and government. The group is also interested in information systems resource management, systems development methodologies and the use of information systems as a competitive advantage and as a tool for decision making at the operational, tactical and strategic levels of an organization. Specific research interest include digital libraries, data warehousing, data mining, information search and retrieval, Web-enabled databases, electronic commerce applications, object-oriented databases and distributed databases; systems development methodologies, enterprise collaboration systems, social, ethical and security issues in information systems, electronic business and decision support systems.2. Multimedia and Computer-Aided Tools Group The Multimedia and Computer-Aided Tools Group is to pursue research and development efforts in educational and other applications of multimedia, computing, communications and connectivity to education and the learning and other work processes in and outside the university. Specific research interest include educationally-oriented programming language tools, online course delivery and management; intelligent tutoring systems and adaptive learning environments; distance learning, collaborative teaching, user interfaces and human computer interaction; CASE tools, applied artificial intelligence, human factors engineering, ergonomics, systems engineering and work flow/schedule optimization.3. Networking and Computer Systems Group The Networking and Computer Systems Group will pursue a variety of research topics related to computer networks and distributed computer systems. The research work combines theoretical foundations with practical applications and will involve interaction with the user community. Specific research interests include network resource management and monitoring, distributed systems and tools; client-server computing; parallel systems; communication protocols for continuous media such as video and audio over the current Internet networks as well as over high-speed networks; multimedia network protocols, extensible operating systems to support multimedia, enterprise computing and connectivity standards.4. Software Engineering and Programming Languages Group The Software Engineering and Programming Languages Group will conduct research in a variety of areas including contemporary programming languages, compilers and software engineering methodologies; concurrent and event driven software. Specific research interest include software architecture, software evolution, and rapid migration; advanced programming languages, including design, semantics, implementations, programming environment tools, collaborative programming, object-oriented programming and prototyping.Research Group Membership and Responsibilitiesท Conducting research and extension services in their respective areas;ท Periodically suggesting updates to the curriculum based on research findings;ท Systematically developing new or improving existing syllabi/course material in subjects adjunct to their respective research areas;ท Carrying out collaborative research and extension services with partners from other academic institutions, industry and government.Research Life Cycle• Definition. Exploratory research defines a new problem, new constraints, new opportunity, or a new approach.• Initial Solutions. Initial algorithms, designs, theorems, programs are developed.• Evaluation of Initial Solutions. Initial solutions are evaluated and refined in isolation.• Comparison of Solutions. Solutions are compared to one another and also to ideal solutions.• Space of Possible Solutions. Theorems are proved about the limits on any solutions. Existing solutions are placed in a common framework to determine whether all possible solutions have been found.• Technology Transfer. Best approaches are transferred to users.

• Not all of these phases are seen in all areas. For units with high cost of evaluation only relatively weak methods can be applied to evaluate initial solutions and compare solutions.• For units with high variety, it is difficult to understand the space of all possible solutions.

Technologies have indeed transformed the life of individuals today and we can all see how it made our daily living more comfortable and easier. It is rightful to give an account to the success of Computer Science Researches. What is research? The Oxford Concise dictionary defines research as: research as a. the systematic investigation into and study of materials, sources, etc, in order to establish facts and reach new conclusions. b. an endeavor to discover new or collate old facts etc by the scientific study of a subject or by a course of critical investigation. This definition is useful because it immediately focuses upon the systematic nature of research. In other words, the very meaning of the term implies a research method. These methods or systems essentially provide a model or structure for logical argument.I found an article related to this topic in the internet which also used as reference of my fellow student taking up this subject as their response to this topic. This article entitled The State of Computer Science Research in the U.S. and The Evolution of Federal Support for It was made by Wm. A. Wulf, Ph.D., the President, National Academy of Engineering and AT&T Professor of Engineering and Applied Science, University of Virginia, presented to House Science Committee U.S. House of Representatives on 12 May 2005.

From this article it stated the importance of having Computer Science Researches activities in one nations, how it will benefits us, why there is a need for us to conducted such researches, how it is done successfully and who needs to cooperate in this said researches.

As I read this article, I can not help not to be envious to those nations implementing such research department unlike here in the Philippines. We all know the importance and significance of the researches; it is vital and essential foundation for the future to problems and to provide possible solutions through critical investigation from the gathered facts. There is a need of the government support for the universities who are conducting such scientific investigation. Collaboration between the universities student, the government and also the industries must be seen in this situation. It is a need for us today to conduct researches; yes somehow this implies financial support, dedicating more time to have successful researches this may take a long time but you see the bigger the support a research can get the wider the horizon it may cover, the more courageous the researcher will be to test new ideas, innovative designs and to implement it in the future given the availability of the resources. And also the longer the time spent for a research the more credible it is. Come to think of it, researches should not be considered as expense rather this should be treated as investment. Investment in the sense that we may not be the one who directly feel and see the benefits of these researches but it is your son’s/daughter’s generation - the future generation. We are now enjoying the product of the studies before now it is our time to invest for the future generation to continue to improve the quality of life.

With research we can be able to form a systematic and arranged investigation to organize facts or gather data, and is often related to a problem that has to be solved. Research is the study of materials, sources, and data in order to get conclusions. Any research is at the center of the process of learning about the world, and it is important that people understand how "good" research is organized. People depend on the accumulated knowledge and experience of the civilization. Research is the process of which civilization uses to construct further on the store of knowledge.

I have read a topic on Research in computer science: an empirical study in this article they have examine the state of computer science research from the point of viewof the following research questions: 1. What topics do CS researchers address? 2. What research approaches do CS researchers use? 3. What research methods do CS researchers use? 4. On what reference disciplines does CS research depend? 5. At what levels of analysis do CS researchers conduct research?

To answer these questions, they examined 628 papers published between 1995 and 1999 in 13 leading research journals in the CS field. The results suggest that while CS research examines a variety of technical topics it is relatively focused in terms of the level at which research is conducted as well as the research techniques used. Further, CS research seldom relies on work outside the discipline for its theoretical Foundations. Findings are presented as an evaluation of the state of current research and as groundwork for future CS research efforts.

Computer science is a well-established discipline that is represented in almost all institutions of higher education. As part of their faculty responsibilities, computer scientists conduct research in several different areas, such as artificial intelligence, databases, distributed, systems, etc. Research is published in journals dedicated to fostering research in those specific areas. Thus, it is not surprising that most papers that examine the nature of research within computer science tend to focus on specific areas of computer science

They also categorized the research techniques used. They divided those techniques into research approach, the overall approach undertaken in performing the research, and research method, the more detailed techniques used.

In the study made it shows that research in computer science is spread evenly among the five categories: computer concepts (28.67%), problem-domain-specific concepts (21.50%), systems/software concepts (19.11%), data/ information concepts (15.45%), and problem-solving concepts (14.65%). Two other categories, systems/software management concepts, and organizational concepts, are represented minimally, while two categories, societal concepts and disciplinary issues are not represented at all.The leading sub-category was computer graphics/ pattern analysis within the problem-domain-specific concepts category. Twenty percent of articles were devoted to this category, while 17.68% were devoted to inter-computer communication (part of computer concepts), which includes such topics as networking and distributed systems. Other notable topics were computer/ hardware principles/architecture at 10.19% (again part of computer concepts) and database/warehouse/ mart organization at 8.44% (part of data/information concepts), while papers focusing on mathematics/computational science (part of problem-solving concepts) were next at 6.69%. It also shows the primary research approaches by journal. The data shows that FP (formulate-process, method, or algorithm) was the most important research approach in 12 of the 13 journals examined while formulate-concept (FC) was the second most important approach (in 8 out of those 12 journals).

It also shows the primary research approaches used by CS researchers. Formulative was by far the dominant research approach representing 79.15% of the papers assessed, followed by evaluative and descriptive approaches, which were virtually equivalent at 10.98% and 9.88%, respectively.Examination of the sub-categories of research approach shows that FP, a multifaceted subcategory that includes formulating processes, procedures, methods, or algorithms is the most important of the formulative subcategories. Approximately half of computer science research (50.55%) fell into this category. The next largest category was FC (e.g., formulating a concept such as a data model), at 17.04%. Papers whose primary focus was evaluation using techniques other than deductive, interpretive, or critical approaches (evaluative-other) were third at 9.87%. It shows the primary research approaches by journal. The data shows that FP (formulate- process, method, or algorithm) was the most important research approach in 12 of the 13 journals examined while formulate-concept (FC) was the second most important approach (in 8 out of those 12 journals)

The study also presented the primary research methods used by CS researchers. Conceptual Analysis/Mathematical (CA/M) (73.41%) was the primary research method with conceptual analysis (not using mathematical techniques) next at 15.13%. Categories such as laboratory experiment (using human subjects), laboratory experiment (software), simulation, and concept implementation are also represented, although none reached double-digits. Table 8 (Panel C) shows the findings for researchmethod by journal. CA/M was the most important research method in all journals except ACM Transactions on Computer–Human Interaction (TOCHI).

It also presented the levels of analysis used by CS researchers. It shows that, similar to research approach and research method, CS research was also relatively focused in terms of levels of analysis. The most dominant level of analysis was the Computing Element (CE) category (53.34%), which relates to algorithms, methods, and techniques, e.g., a scheduling algorithm for a crossbar switch. The Abstract Concept category, which relates to concepts such as the definition of global predicates in the context of distributed computations, was the next largest at 38.85%. Finally, 5.57% of the papers focused on the computing system (CS) level. Two other categories (individual (IN) and profession (PRO))were below 2%, while the five categories of societal, organizational context, external business context, project, and group/team were not represented. It was presented that the level of analysis by journal.The data shows that CE was the primary level of analysis in 8 of the 13 journals. The figures ranged froma low of 51.69% in IEEE Transactions on Pattern Analysis and Machine Intelligence to a high of 88.24%in IEEE Transactions on Visualization and Computer Graphics (VCG). Further, AC was the primary level of analysis in four journals ranging from 42.86% to 56.04%, while Individual was the primary level of analysis in ACM Transactions on Computer–Human Interaction (TOCHI). In addition, TOCHI and ACMTransactions on Graphics (TOG) were the only journals to publish articles that used a non-technical level of analysis (i.e., levels of analysis other than AC, CS 6 or CE) with 40% of the articles in TOCHI and 6.45% of the articles in TOG focusing on the individual level. The reference disciplines used by CS researchers were showed. The results suggest that, for the most part, CS research does not rely on other fields for its fundamental theories and/or concepts. Of the papers examined, Computer Science itself was the reference discipline in 89.33% of the cases. The only other discipline that emerged was mathematics (8.60%). There were trivial instances of papers that relied on cognitive psychology (0.80%) and science (0.96%).breakdown of reference discipline by journal was presented. Not surprisingly, computer science was the primary reference discipline in all journals, ranging from a low of 57.69% in Journal of the ACM (JACM) to a high of 100% in IEEE Transactions on Parallel and Distributed Systems. Mathematics was a major reference discipline in JACM with 41% of the articles using concepts directly from that discipline. Only two journals did not have mathematics as their second most important reference discipline (TOCHI and VCG). Cognitive psychology emerged as a major reference discipline in TOCHI (20%) and Science in VCG (17.65%).

It was characterized that CS research in terms of the topics, research approaches, research methods, levels of analysis, and reference disciplines used. The results suggest that CS research focuses on a variety of technical topics, using formulative approaches to study new entities that are either computing elements or abstract concepts, principally using mathematically-based research methods.The results from our study should be of value to both researchers and doctoral students engaged in computer science research.

Let me just first share to you insights on what computer science is. As stated in the Wikipedia, Computer science (or computing science) is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that describe and transform information. According to Peter J. Denning, the fundamental question underlying computer science is, "What can be (efficiently) automated?". Computer science has many sub-fields; some, such as computer graphics, emphasize the computation of specific results, while others, such as computational complexity theory, study the properties of computational problems. Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing computations, while computer programming applies specific programming languages to solve specific computational problems, and human-computer interaction focuses on the challenges in making computers and computations useful, usable, and universally accessible to people. However, the focus of computer science is more on understanding the properties of the programs used to implement software such as games and web-browsers, and using that understanding to create new programs or improve existing ones. As a discipline, computer science spans a range of topics from theoretical studies of algorithms and the limits of computation to the practical issues of implementing computing systems in hardware and software. The Computer Sciences Accreditation Board (CSAB) – which is made up of representatives of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers Computer Society, and the Association for Information Systems – identifies four areas that it considers crucial to the discipline of computer science: theory of computation, algorithms and data structures, programming methodology and languages, and computer elements and architecture. In addition to these four areas, CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.

The prediction that computers will be increasingly important in our schools, offices, and homes has become a cliché. Word-processing, electronic mail, databases, spreadsheets, analytic tools, and telecommunications have allowed researchers, office workers, and families to have access to a resource that was previously the territory of government, big businesses, and large universities. The way we live and work is being changed and enhanced by improved access to public databases, increased availability of sophisticated computational software, and world-wide communications facilities at a relatively modest price. Artificial intelligence, particularly robotics and expert systems, is a field of computer science that will have a powerful impact on our culture in the near future. What some have perceived as a revolution, however, is actually an evolution of the influence of computing on our society over the past 40 years. Though several generations of computers have matured during this period, their distinctions are not at all clear, primarily because they provide a continuum of capabilities, rather than a succession of preemptive advances. Thus microcomputers, the most recent result of this process, do not replace their mainframe and minicomputer predecessors, function concurrently and complimentarily with them.

Latanya Sweeney from the Carnegie Mellon University stated that Computer Science research and practice are raising growing privacy concerns among the public and government. Computer technology’s increasing ability to capture, organize, interpret and share data about individuals raises questions about what privacy practices computer science researchers should adopt, if any. Not all areas of computer science research are affected by privacy issues. In the crudest classifications possible, computer science research can be divided into: (1) theoretical computer science, which has a close relationship to logic and mathematics; (2) programming languages and systems, which concerns the general development and operation of physical computer systems and networks; and, (3) artificial intelligence (AI), which has a long-term vision of producing machines that can think, reason and function comparable to humans

Most of the research facing privacy concerns fits into the crudely classified third group, AI. In more fine-grained classifications, computer science research involving human-computer interaction, personal robots and assistants, biomedical applications, data mining, sensor technology, ubiquitous computing, cybersecurity, and data privacy (a new emerging area aimed at providing technical solutions to privacy problems) are more likely today to face privacy controversies than are any other research areas in computer science.Two kinds of privacy issues arise in computer science research: (1) privacy issues inherent in applications of developing technology; and, (2) privacy issues related to information or practices needed to develop technology. This shift in computer science research is due in great part to two trends: (1) the field’s increasing ability to capture and share large volumes of person-specific information and (2) the field’s increasing development of methods to use that information to develop more useful machines.Latanya Sweeney also pointed out that if developments in computer technology have raised privacy issues, then many believe computer technology can be instrumental in resolving them.

Another article related on Computer Science research also discussed the state of computer science research in India. India prides itself in having one of the largest technical manpower in the world. Her software industry has seen tremendous growth -- over 50% each year during the last 10 years -- which is the envy of many software exporting countries throughout the world. The students from India's top science and technology educational institutions are highly sought after by research universities in the US and Europe. Computer Science (CS) research in India started in earnest only in the mid-80's triggered by the establishment of post-graduate programs in many institutions throughout the country at that time. Today, almost all areas of computer science research are covered by researchers in India, including topics that are "hot" elsewhere such as multi-media, workflow automation, virtual reality, and hardware-software co-design. Some of the research has even attracted international attention including work on neuro-fuzzy systems, machine learning, genetic and neural algorithms, the modeling and control of flexible manufacturing systems, speech synthesis, databases, and complexity theory. There are many in Indian computer science who argue that the goals of research and development in India ought to be manpower development, increasing competence, and keeping faculty up-to-date with current techniques. Towards this end, it is said that "reinventing the wheel" is not only necessary but also important. This might be one of the reasons that even though it is said (repeatedly) that India has one of the world's largest technical manpower, the manpower needed to do state-of-the-art research is found to be wanting, both in quality and quantity.

Without Computer Science-sponsored research, complex, inefficient computer systems could overwhelm scientists. The software industry is unlikely to commit to long-term research or to develop programming for the relatively few machines equipped with tens to hundreds of thousands of processors. Yet, these powerful computers and the applications that run on them are vital to maintaining the United States’ competitiveness in the world economy. Computer Science research will focus on scalable software and applications that can weather system reliability. Such efforts are pushing computer science into unknown realms of discovery.

Various topics on computer science research have been mentioned in the previous paragraphs but I think the current topic which I considered to be really relevant nowadays are those that pertain to the environment which topics are usually termed as “green”.

Computer Science is the systematic study of the feasibility, structure, expression, and mechanization of the methodical processes (or algorithms) that underlie the acquisition, representation, processing, storage, communication of, and access to information, whether such information is encoded in bits and bytes in a computer memory or transcribed in genes and protein structures in a human cell.

Computer Science is not just about building computers or writing computer programs! Computer Science is no more about building computers and developing software than astronomy is about building telescopes, biology is about building microscopes, and music is about building musical instruments! Computer science is not about the tools we use to carry out computation. It is about how we use such tools, and what we find out when we do. The solution of many computer science problems may not even require the use of computers—just pencil and paper. As a matter of fact, problems in computer science have been tackled decades before computers were even built. That said the design and implementation of computing system hardware and software is replete with formidable challenges and fundamental problems that keep computer scientists busy. Computer Science is about building computers and writing computer programs, and much much more!

Computers and software artifacts have become indispensable tools for the pursuit of pretty much every scientific discipline. The use of computers has enabled biologists to comprehend genetics, has enabled astrophysicists to get within femtoseconds of the big bang's initial conditions, and has enabled geologists to predict earthquakes. It is not surprising, then, for scientists in these disciplines to increasingly rely on a computational methodology (in addition to traditional mathematical or empirical methodologies) to make advances in their respective fields of study. Such scientists are often referred to as computational scientists. So, a computational chemist is a scientist who uses computers to make contribution to chemistry, just as mathematical physicist uses mathematics to model atomic dynamics, or an empirical biologist uses a microscope to observe cellular behaviors. And, just like all of these scientific disciplines, advances in computer science itself often rely on the use of computers and computational processes. In that sense, among all scientific disciplines, Computer Science is unique. It is the only discipline which fuels its own advancement. Indeed it is a recursive discipline!

The realization of a computing system, subject to various physical and technological constraints, is a challenging undertaking that requires a great deal of knowledge about the functionality and characteristics of the building blocks available at our disposal using today's technologies (e.g., semiconductor technologies, optical communication technologies, wireless signaling technologies, etc.) Computer engineering concerns itself with current practices in assembling hardware and software components to erect computing engines with the best cost-performance characteristics. In contrast, computer scientists worry about the feasibility and efficiency of solutions to problems in a manner that is less dependent on current technologies. As such, computer scientists work on abstractions that hide details of underlying implementations to enable the construction and comprehension of yet more complex systems. The creative process of developing, implementing, and evaluating computing abstractions is what pushes the frontiers of what computers and computations can do. For example, the pervasive use of the Web in our society is a direct result of our ability to free Internet application developers from the lower-level implementation details of moving bits and bytes over wires from one point to another. Similarly, the tremendous advances in the use of computer animation are a direct result of our ability to free programmers from having to worry about lower-level digital signal processing techniques.

Now the question is what is the current state of computer science research? Researches in computer science as I mentioned earlier are more on developing new ways on how to make life easier. Computer scientist researches on new algorithms and the like to improve our way of life. Especially in this age of technology computer science researches plays a very important part. Computer science research scope is very broad and every research may be essential in every fields of knowledge. Presently, because of current problems of the environment there are lots of researches that focus on benefiting the environment through the use of technology. They often call it as “green computing”, green computing is a new innovation on the field of computer science research with concerns focusing on minimizing the effect of the technology.

Some fields in computer science research

Algorithms• formal processes used for computation, and the efficiency of these processesApplications• design and development software for everyday useArtificial intelligence• implementation and study of systems that exhibit (either behaviorally or seemingly) an autonomous intelligence or behavior of their own, sometimes inspired by the characteristics of living beings. Computer science is closely tied with AI, as software and computers are primary tools for the development and progression of artificial intelligenceCompilers• ways of efficiently translating algorithms from one form (usually a programming language) to anotherComputational complexity theory• fundamental bounds (esp. time and storage space) on computationsComputer programming• the act of writing algorithms in a programming languageComputer graphics• algorithms both for generating visual images synthetically and for integrating or altering visual and spatial information sampled from the real worldComputer vision• algorithms for extracting three dimensional objects from a two dimensional pictureCryptography• algorithms for protecting private data, including encryptionData mining• the process of sorting through large amounts of data and picking out relevant information.; closely related to information retrievalData structures• the organization and storage of dataNetworking• algorithms and protocols for reliably communicating data across long distances, often including error correctionOperating systems• systems for managing computer programs and data structuresProgramming languages• formal languages for expressing algorithms and the properties of these languagesRobotics• algorithms for controlling the behavior of robotsScientific computing• algorithms for use in the sciences, especially (but not exclusively) biology (as in bioinformatics), physics, and chemistrySoftware engineering• the process of designing, developing, and testing programsSteganography• algorithms for covertly hiding data in seemingly unrelated documents, such as graphicsType Theory• formal analysis of the types of data, and the use of these types to understand properties of programs, especially program safety